Power conservation is a vibrant area of research on wireless sensor networks. Several research papers have shown that using mobile sync in the sensor field, which collects data from sensor nodes via single or multi-hop communication, can save significant energy. However, sinks move slowly, which increases sensor network delays, especially in delay-sensitive applications. To address this issue, various rendezvous-based techniques are described in which a subset of sensor nodes are selected from the field as rendezvous points (RPs). The remaining nodes transfer the captured data to the next RP, where the data is buffered. The RP is then used to build a path for the mobile sink to tour and collect the buffered data. This article describes various rendezvous-based techniques and analyzes their strengths and weaknesses in terms of energy savings.

In recent years IoT has developed very rapidly. IoT devices are used to monitor and control physical objects to transform the physical world into intelligent spaces with computing and communication capabilities. Compared to cloud computing, fog computing is used to support latency-sensitive applications at the edge of the network which allows client requests to be processed faster. This study aims to propose a monitoring framework for containerized black box microservices in a fog computing environment to evaluate CPU overhead, as well as to determine the operating status, service characteristics, and dependencies of each container.
This study proposes a monitoring framework to integrate computing resource usage and run-time information from service interactions using a black box approach that seeks to integrate service-level information and computing resource information into the same framework. The proposed framework is limited to observing information monitoring after the server receives a request. This study uses JMeter to simulate user actions, which send requests to the server, and this research assumes the user knows the IP address of the server. For container monitoring methods in fog computing, all are indirect monitoring methods.
The results of this study indicate that the proposed framework can provide operational data for visualization that can help system administrators evaluate the status of running containers using a black box approach. System administrators do not need to understand and modify target microservices to gather service characteristics from containerized microservices. Regarding future research, it is suggested to expand the exploration of modified system information, and that part of the container management tool code can be pre-tried so that the framework proposed in this study can provide real-time quantitative indexes for the load balancing algorithm to help optimize the load balancing algorithm.

This study aims to examine the role of Strategic foresight and its capability to support the development of management innovation processes within organizations. This study uses a narrative literature review approach involving potential interactions of three main topics, namely: strategic foresight, management innovation, and management cognition. The research findings explain that every individual has a character from birth to being able to see the future. Then the capability for foresight in this organization must be developed and continuously maintained by both stakeholders in the organization's management and employees. Before implementing a foiresight strategy, it is necessary to understand in depth managerial cognition as the basis for its application. Furthermore, the development of a well-managed strategic foresight will become a management innovation so that it can maintain the sustaincapability of the organization. This conceptual paper lays a foundation that can be used as further research in determining strategic foresight abilities in relation to managerial dynamic abilities. The results of this paper can be used by organizations with a long history of facing challenges in capturing the challenges of changing business environment in the future.

Peer-to-peer systems nowadays are widely used because of the scalability and high reliability. File replication and consistency maintenance are widely used techniques to achieve high system performance. These techniques are connected to each other. The connection of these techniques is consistency maintenance is needed in file replication to keep the consistency between a file and the replicas. Traditional file replication and consistency maintenance methods need a high cost. The usage of IRM (Integrated file Replication and Consistency Maintenance inP2P systems) which will achieve high efficiency at a significantly lower cost can be used to solve this problem. IRM reduces redundant file replicas, consistency maintenance overhead, and unnecessary file updates.

This study aims to determine the role of work environment, motivation, job satisfaction, and organizational commitment in improving the Organizational Citizenship Behavior (OCB) for the employee at the PT Garudafood Putra Putri Jaya Tbk of Gresik area. The research method applied is quantitative, using path analysis and the Sobel test to examine the relationship and the magnitude of the contribution of influence between each variable. The number of respondents in this study was 200 employees.The results showed that the work environment and motivation significantly positively affected job satisfaction. Meanwhile, work environment, motivation, and job satisfaction positively and significantly affect organizational commitment. It was found that communication between superiors and subordinates is an essential factor for improving OCB, so further research is needed on the effect of leadership style on OCB

The purpose of this study was to examine the effect of marketing innovation, product innovation, and cafe atmosphere on purchasing decisions in F&B MSMEs. The sampling technique used was purposive sampling. The research uses qualitative methods with a descriptive approach and quantitative methods in data processing for hypothesis testing. Hypothesis testing uses a structural regression approach with Smart-PLS 3.0 software using the t-test at a significance level of 5%. The choice of software is because this study uses path analysis with a sample size of 75 F&B MSMEs consumers in Malang City

IoT technology is useful for chicken farming to control the condition of the farm concerning some problems such as odour, temperature fluctuations and feeding time system. This study used MQ135 to detect ammonia odour level, DHT11 to check room temperature, and RTC3231 to regulate feeding time. The data obtained from the sensor was sent by wemos to the fire base and MySQL to be read on android so that it can be monitored directly by the breeder. When the ammonia level is above normal it will turn on the odour fan. If  DHT11 reaches the value above 300C, it will turn on the cooling fan, and turn on the heating light when the temperature is below 250C. As RTC3231 sets the time at 07.00 and 14.00, the chicken feeder will automatically open to feed the chickens according to the time set. Table 1 and 2 show that the experiment obtained a value of 100% working well. This study succeeded in monitoring environmental conditions through Android and executing automatic feeding at the predetermined time. Thus, it can be concluded that the use of IoT technology for monitoring and feeding system automation  in chicken farms is highly recommended.

The main threat by comparable methods lately is the temporary downtime for accurate-current network dispatch errors. Throughout a temporary outage, Power Electronic based power sources stop operating, giving rise to possible security defiance towards the network, in this research, the potentially viable choice to serve continuous work temporarily for the scheme is provided with consideration of identifying upgrades to existing photovoltaic generators (photovoltaic generators discrete) and an upgrade in the separate establishment of existing “photovoltaic” and “Energy Storage Systems” discrete hybrid photovoltaics. This study aims to find a series of power sources with Power Electronic interfaces that are connected to a low “Short Circuit Ratio” network and “Low Inertia” grid to operate without a moment's stoppage.
The proposed method was proved by adopting PSS/e on a method where power electronics-occupying assets produce the majority of energy. Inverter models along with temporary shutdown through an equal 3-period fault were advanced in PSS/e. together with increasing infiltration of “Power Electronics” established multitude and resources, progressive completion is needed to improve network stability in low a) areas and low inertia networks. The requirements for progressive solvent arose out of the steady variation in the paradigm of the power grid from the dominant systems of traditional electric machines to the high penetration of systems based on power electronics. A technical comparison was made between distinct categories of resolution (divergent photovoltaic and divergent hybrid photovoltaic) to operate a photovoltaic generator's weak “Short Circuit Ratios” also “Low Inertia” grating (grid).
The results of this study indicate that the proposed solution is calculated nether disparate running term and error class adopting the Electromagnetic Transient model. Moreover, to analyze distinct solvents, a specialized proportion is served on discrete hybrid photovoltaic generators. The proposed solution is the development of conventional increase as well as contemporary condensers, deter capacitors, and reducers to advanced photovoltaic generators and hybrid photovoltaic generators to provide voltage support to ensure continuous working through lopsided dispatch streak disturbances, and another solution is photovoltaic-energy generation. Integrated storage system connected to High Voltage dc and high voltage ac transmission network.

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis.
The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets.
The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.

This paper aims to investigate how the effect of Assets Structure and Firm Size on Firm Value Mediated by Capital Structure in Non-Financial Sector Companies Listed on the Indonesia Stock Exchange period 2013-2021. The research method used in this research quantitative An empirical research was conducted with  a quantitative approach using panel regression OLS to estimates the dirrect effect and Partial Least Squares Structural Equation Modeling (PLS-SEM) to estimates indirect effect, by using STATA statistical software. sample selection using purposive sampling and found a sample of 180 companies. From the analysis it was found that capital structure and asset structure have no effect on firm value, Firm size has a negative significant on firm value , asset structure has a negative significant on capital structure, firm size has a positive significant  effect on capital structure. In addition, capital structure is able to mediate the relationship between asset structure and firm size on firm value. Empirical studies conducted usually only look at the direct effect of the independent variable on the dependent variable, but in this study examines the direct and indirect effects of the independent variables on the dependent variable. In addition, this study does not only use samples from 1 company sector, but using all non-financial sectors companies listed on the Indonesia Stock Exchange